|Publication number||US7117222 B2|
|Application number||US 10/388,091|
|Publication date||Oct 3, 2006|
|Filing date||Mar 13, 2003|
|Priority date||Mar 13, 2003|
|Also published as||US20040181533|
|Publication number||10388091, 388091, US 7117222 B2, US 7117222B2, US-B2-7117222, US7117222 B2, US7117222B2|
|Inventors||John M. Santosuosso|
|Original Assignee||International Business Machines Corporation|
|Export Citation||BiBTeX, EndNote, RefMan|
|Patent Citations (11), Non-Patent Citations (2), Referenced by (25), Classifications (18), Legal Events (5)|
|External Links: USPTO, USPTO Assignment, Espacenet|
1. Field of the Invention
The present invention generally relates to processing data and more particularly to enhancing the performance of a client through the utilization of statistical information regarding the distribution of requested data to be processed by the client.
2. Description of the Related Art
Databases are computerized information storage and retrieval systems. A relational database management system is a computer database management system (DBMS) that uses relational techniques for storing and retrieving data. The most prevalent type of database is the relational database, a tabular database in which data is defined so that it can be reorganized and accessed in a number of different ways. A distributed database is one that can be dispersed or replicated among different points in a network. An object-oriented programming database is one that is congruent with the data defined in object classes and subclasses.
Regardless of the particular architecture, in a DBMS, a requesting entity (e.g., a client or client application) demands access to a specified database by issuing a database access request. Such requests may include, for instance, simple catalog lookup requests or transactions and combinations of transactions that operate to read, change and add specified records in the database. These requests are made using high-level query languages such as the Structured Query Language (SQL). Illustratively, SQL is used to make interactive queries for getting information from and updating a database such as International Business Machines' (IBM) DB2, Microsoft's SQL Server, and database products from Oracle, Sybase, and Computer Associates. The term “query” denominates a set of commands for retrieving data from a stored database. Queries take the form of a command language that lets programmers and programs select, insert, update, find out the location of data, and so forth.
Generally, the DBMS includes a query optimizer component configured to determine the manner in which queries will be processed. The primary task of the optimizer is to determine the most efficient way to execute each particular query against a database. To this end, the optimizer typically determines an access plan for use in executing the query against the database. In general, the access plan contains low-level information indicating precisely what steps the system is to take to execute the query. Commonly, the access plan calls for the use of one or more indexes carefully designed to speed execution of the query. Database indexes provide a relatively quick method of locating data of interest without a full sequential search through the table, which would entail accessing each row.
In general, indexes provide statistical information regarding distribution of the data within a particular database field, such as a particular column of a relational database. Examples of the type of statistical information provided by an index include the number of distinct values stored in a column and the number of occurrences of each distinct value within the column. The optimizer may use this statistical information to decide whether to use indexes and/or which indexes to use. For example, the index may indicate that a relatively small number of distinct values occur in a column of a table having a relative large number of rows. Therefore, the optimizer may access the index to determine which rows has a requested value. In such a case, the use of indexes typically results in a considerable reduction in the total number of I/O requests that must be processed in order to locate the requested data. On the other hand, if the number of distinct values is large relative to the total number of rows, a full sequential search for the requested data may be more efficient.
Commonly, a client requesting the data must perform a number of formatting operations after receiving the requested data. For example, the client may be required to convert a field from one format (e.g., a string of characters) to another format (e.g., an integer) for use in a particular operations performed by the client. In some cases, the statistical information contained in indexes may be used to enhance the performance of such formatting operations. For example, if a column contains a relatively small number of distinct values (as in the case described above), the client may store locally (e.g., in a cache) each of the distinct values in the converted format. Rather than perform the formatting operations each time one of the values is retrieved from the column, the client may simply retrieve the formatted value from the cache, thus reducing the processing overhead of formatting (creating a new object to hold the formatted value, converting the data, etc.).
However, conventional use of indexes has been limited to optimizing access of data from the database and does not extend to the requesting client. Accordingly, there is a need for an improved method of enhancing performance of a requesting client through the use of statistical information, such as that commonly contained in database indexes.
The present invention generally provides methods, articles of manufacture and systems for enhancing the performance of applications requesting data from a database by utilizing statistical information regarding the requested data.
For some embodiments, a client may access statistical information regarding the data, such as that commonly contained in indexes (e.g., encoded vector indexes), conventionally generated for use by a query optimizer. Based on the statistical information (e.g., if distinct values from a field or column of the database are likely to be returned often), the client may generate and cache pre-formatted data records containing pro-formatted data corresponding to distinct values of data stored in the database. Rather than format each distinct value as it is received from the database, the client may retrieve the pre-formatted data corresponding to the distinct value from the pro-formatted data records, thereby avoiding repeatedly formatting the same distinct value.
For some embodiments, based on the statistical information regarding the data, the client may request that the server send small byte-code representations of data from the database, rather than the actual data. The small byte-code representations may be significantly smaller than the actual represented data, thus reducing network traffic between the client and server. The client may then retrieve the actual represented data from a corresponding data representation record.
For some embodiments, a method for use by a client in accessing and manipulating data from a data source generally includes obtaining information regarding one or more distinct data values of a first format stored in a field of a data source to be queried by the client and, based on the information, generating one or more data objects, each containing one of the distinct values and a corresponding pre-formatted data value of a second format.
For some embodiments, the article of manufacture generally includes a computer-readable medium containing a program which, when executed by a processor, performs operations for accessing and manipulating data from a data source. The operations generally include obtaining information regarding one or more distinct data values of a first format stored in a field of a data source to be queried by the client and, based on the information, generating one or more data objects, each containing one of the distinct values and a corresponding pre-formatted data value of a second format.
For some embodiments, the system generally includes a database having at least one field with one or more distinct values stored therein and a client system. The client system generally includes a cache, one or more pre-formatted data records contained in the cache, each pre-formatted data record containing one of the distinct values and corresponding pre-formatted data, and an application. The application is generally configured to receive, from a server of the database, data comprising at least one of the distinct values, and to retrieve, from a corresponding one of the pre-formatted data records, pre-formatted data associated with the distinct value received from the server.
So that the manner in which the above recited features, advantages and objects of the present invention are attained and can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to the embodiments thereof which are illustrated in the appended drawings.
It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and are therefore not to be considered limiting of its scope, for the invention may admit to other equally effective embodiments.
The present invention generally provides methods, articles of manufacture and systems for enhancing the performance of a client or client application by utilizing statistical information regarding data requested thereby. In some embodiments, the statistical information may be contained in commonly used database objects, such as a indexes. However, rather than confine the use of the statistical information contained in such objects to a query optimizer, as in conventional systems, the present invention extends the use of the statistical information to the requesting client. Through this extension, the requesting client may advantageously utilize techniques, such as column level caching to reducing formatting operations and associated processing overhead. According to another aspect of the present invention, the statistical information may be utilized to reduce network traffic between the requesting client and a database server. For example, the database server may send relatively small representations of large data values, rather than the actual values, thus consuming less network bandwidth. In other words, the user of representations may allow a larger number of records to be returned by the server in a single block. The client may then retrieve the actual values from a locally cached table, based on the received representations.
As used herein, the term client generally refers to an application that runs on any type of computer system (e.g., a personal computer, workstation, handheld computer, etc.) that relies on a server to perform some operations. The term server generally refers to an application that performs operations for a client (e.g., a database server processes queries issued by a client). The terms client and server may also refer to the respective machines (e.g., computer systems) running the client and server applications. However, the client and server applications may also reside on the same machine.
As used herein, the term database generally refers to any collection of data, regardless of the particular physical representation (or “schema”) and the terms database and data source may be used interchangeably. The term schema generically refers to a particular arrangement of data. In other words, a database may be organized according to a relational schema (accessible by SQL queries), an XML schema (accessible by XML queries), or any other schema presently known or to be developed. As used herein, the term field (also commonly referred to as an entity) generally refers to any object about which data can be stored. Accordingly, the exact form of a field may depend on the particular physical data representation of the underlying database. For example, in a relational data representation, a field commonly takes the form of a column in a table.
Embodiments of the present invention may be used to advantage when accessing and manipulating data stored in any type fields from any type database regardless of the underlying schema. When accessing and manipulating the data, statistical information regarding the data may be collected from the database. The statistical information may be stored in any type of data object including, but not limited to, any type of database index, such as bitmap indexes, binary tree indexes, radix indexes, encoded vector indexes (EVIs), or any other type of indexes presently known or to be developed. However, to facilitate understanding, embodiments of the present invention will be described below with reference to column-level information contained in EVIs as a specific, but not limiting example, of a type of statistical information
One embodiment of the invention is implemented as a program product for use with a computer system such as, for example, the client computer system 110 (referred to hereinafter as client 110) of the data processing environment 100 shown in
In general, the routines executed to implement the embodiments of the invention, may be part of an operating system or a specific application, component, program, module, object, or sequence of instructions. The software of the present invention typically is comprised of a multitude of instructions that will be translated by the native computer into a machine-readable format and hence executable instructions. Also, programs are comprised of variables and data structures that either reside locally to the program or are found in memory or on storage devices. In addition, various programs described hereinafter may be identified based upon the application for which they are implemented in a specific embodiment of the invention. However, it should be appreciated that any particular nomenclature that follows is used merely for convenience, and thus the invention should not be limited to use solely in any specific application identified and/or implied by such nomenclature.
Referring now to
The client 110 could include a number of operators and peripheral systems as shown, for example, by a mass storage interface 137 operably connected to a direct access storage device (DASD) 138, by a video interface 140 operably connected to a display 142, and by a network interface 144 operably connected to the one or more networked devices 146 and the database server 147. The display 142 may be any video output device for outputting viewable information. The networked devices 146 may be any combination of any type networked devices, such as, networked printers and network accessed storage (NAS) devices. The database server 147 may be used to access (e.g., serve) data from a database 148.
The client 110 is shown comprising at least one processor 112, which obtains instructions and data via a bus 114 from a main memory 116. The processor 112 could be any processor adapted to support the methods of the invention. The main memory 116 is any memory sufficiently large to hold the necessary programs and data structures. Main memory 116 could be one or a combination of memory devices, including Random Access Memory, nonvolatile or backup memory, (e.g., programmable or Flash memories, read-only memories, etc.). In addition, main memory 116 may be considered to include memory physically located elsewhere in a client 110, for example, any storage capacity used as virtual memory or stored on a mass storage device (e.g., DASD 138) or on another computer coupled to the client 110 via bus 114.
The main memory 116 is shown configured with an operating system 118. The operating system 118 is the software used for managing the operation of the client 110. Examples of the operating system 118 include UNIX, Microsoft Windows®, and the like. As illustrated, the main memory 116 further includes at least one application 120 with an application optimizer 122. The application 120 is a software product comprising a plurality of instructions that are resident at various times in various memory and storage devices in the client 110. When read and executed by one or more processors 112 in the client 110, the application 120 causes the client 110 to perform the steps necessary to execute steps or elements embodying various aspects of the invention.
For some embodiments, the application 120 is generally configured to send queries to the database server 147 to access data from the database 148. While shown as separate from the client 110, for some embodiments, the client 110 and database server 147 may reside on the same computer system. In either case, the application optimizer 122 is generally configured to enhance performance of the application 120 in processing data received from the database 148 by accessing statistical information regarding distribution of the data in the database 148. As previously described, the format of the statistical information may depend on the underlying physical representation of the database 148. For example, if the database 148 has a relational physical representation, the statistical information may take the form of column level statistics 149 describing the distribution of data among columns within tables of the database 148.
As illustrated in
The other component of the EVI 180, the vector 184, contains a byte code value for each entry in the column (i.e., each row in the relational table). This byte code corresponds to the code in the symbol table and represents the actual column value found in the respective row in the database table. The byte codes are in the same ordinal position in the vector 184, as the row it represents in the table. In other words, in the illustrated example, a “1” in the first position of the vector 184 indicates the first row of the database table has an entry for “Alabama” in the state column. The query optimizer 152 may use the symbol table 182 to obtain statistical information about the data for the column associated with the EVI. If the optimizer 152 decides to use the EVI 180 to process the query, the vector 184 may be used to build a dynamic bitmap, which contains one bit for each row in the table. If a row satisfies the query (e.g., a match between a condition and the value in the column, as indicated by the code in the vector 184), the bit is set on. If the row does not satisfy the query, the bit is set off. Similar bitmaps may be generated for other conditions of the query (using other indexes 180 generated over those columns). The bitmaps may then be ANDed together to determine which rows satisfy all of the corresponding query conditions.
In summary, the index 180 may include, among other things, the following statistical information: the type and size of data stored in the column, the number of distinct values stored in the column, and the number of occurrences of each distinct value. Referring back to
The application optimizer 122 is a software component (e.g., a driver) included or associated with the application 120 and generally configured to optimize the manipulation (e.g., formatting, processing, etc.) of data retrieved from the database 148 by the application 120 based on the statistical information regarding the data, such as the type of statistical information that may be stored in the indexes 180. The application optimizer 122 may access the indexes 180 using any suitable technique, such as using a call level interface to the database 148. Examples of common call level interfaces include the Open Database Connectivity (ODBC) and Java Database Connectivity (JDBC™) call level interfaces.
For some embodiments, in an effort to improve efficiency of the application 120, indexes may be created specifically for columns to be accessed by the application 120. For example, while indexes are typically created over columns that are likely to be searched in order to assist the query optimizer 152 in determining a search strategy, according to the present invention, indexes may be created over columns that are likely returned as query results in order to assist the application optimizer 122 in generating various data objects that may improve the efficiency with which the application 120 manipulates data retrieved from the columns.
The various data objects may include a column status table 162, a pre-formatted columns table 164, and a column representations table 166, shown in
If the caching of pre-formatted column values is enabled, rather than manually format a data object retrieved from the database 148, the client 110 may retrieve a pre-formatted data object from a corresponding pre-formatted column record 165 in the pre-formatted column records table 164. Thus, caching pre-formatted column values may reduce processing overhead associated with formatting. As an example, the client 110 may be required to retrieve a date from the database 148 for display to a user. While the date may be stored in a DATE column of the database 148 as a byte string, for example, the client 110 may be required to format the date to a standard readable format. As illustrated in
If the use of data representations is enabled, rather than send potentially large (e.g., many bytes) requested data entries, the server 147 may send smaller (e.g., fewer bytes) representations of the data entries, thus increasing the number of rows that may be transferred per block and reducing network traffic between the server 147 and client 110. The client 110 may then retrieve the actual data entries from the column representation table 166. As an example, upon receiving a single byte-code representation “01” for a state, the client may retrieve the actual state name “Alabama” from a column representation record 167, such as that illustrated in the column representations record table 166 of
The concepts of pre-formatted column caching and the use of data representations may be further explained with reference to
At step 304, a determination is made as to whether the column has been accessed before, for example, within a predetermined time period or since the application 120 has been invoked. If the column has not been accessed before, statistics for the column are retrieved, at step 306, for example, by accessing an index 180 for the column, and a status record 163 corresponding to the column is updated (and/or created, if necessary) based on the column-level statistics.
Once the column level statistics have been retrieved and the corresponding column status record 163 has been updated (or if the column had been accessed before), processing proceeds to step 308 to retrieve data from the server 147. For example, an appropriate query may be sent to the server 147 to retrieve the requested data.
At step 310, the client 110 determines whether the data retrieved from the server 147 is the actual requested data or a representation of the requested data, for example, by checking the corresponding flag in the column status record 163. If the retrieved data is a representation of the requested data, the actual requested data is retrieved from the column representations table 166, at step 312. For example, the client 110 may search the column representations table 166 for a column representation record 167 with a representation field that matches the representation sent by the server 147.
Once the client has the actual requested data (whether received directly from the server 147 or retrieved from the column representations table 166), a determination is made, at step 314, as to whether pre-formatted caching is enabled for the column. As previously described, the determination may be made by examining (the pre-formatted enabled flag of) the column status record 163 for the column. If pre-formatted caching is not enabled, the data is formatted at step 316, and the formatted data is returned (e.g., to the application 120 for further processing), at step 326.
If pre-formatted caching is enabled, at step 318, a determination is made as to whether a pre-formatted record 165 already exists for the retrieved data in the pre-formatted column table. If so, the pre-formatted data object is retrieved from the corresponding pre-formatted record 165 for the column value returned, and the pre-formatted data object is returned, at step 326. If a pre-formatted record 165 does not exist for the retrieved data, the data is formatted, at step 322, and a pre-formatted record 165 containing the formatted data is added to the pre-formatted column table 164, at step 324, prior to returning the formatted data, at step 326. In other words, the first time a new column value is returned, the client 110 may generate a new pre-formatted column record 165, which may be used the next time the same column value is returned.
As previously described,
For some embodiments, a determination of whether any distinct value of a column is likely to be returned relatively often may be made by examining the number of distinct values in the column. For example, a predetermined threshold value may be defined. If the number of distinct values is below the threshold value, it may be determined that at least some of the distinct values will be returned relatively often. The predetermined threshold (NTHRESHOLD) may be set relative to a total number of entries (rows) for the column. As an example, referring back to
For other embodiments, rather than examine only the number of distinct values in the column, the number of occurrences (e.g., as indicated by the COUNT field in the symbol table 182 of
The operations 400 begin, at step 402, by retrieving statistics for a column for which data is to be retrieved. At step 404, a determination is made (for example, as described above) as to whether any of the distinct values of the columns are likely to be returned relatively often. If it is determined that none of the distinct values of the column are likely to be returned relatively often, the advantages to pre-formatted caching and/or the use of data representations for that particular column may not justify the overhead in creating the necessary tables. Therefore, at step 412, pre-formatted caching is disabled for the column and, at step 414, the use of representation for the column is disabled, for example, by clearing the respective flags for these features in the column status record 163.
If it is determined that at least some of the distinct values of the column are likely to be returned relatively often, pre-formatted caching is enabled, at step 406. At step 408, the size of the column is examined to determine if the use of representations should be enabled for the column. If the column is relatively large, the use of representations is enabled, at step 410. For example, the size (in bytes) of the column may be compared to the number of bytes required to represent the distinct values in the column. Again, using the states column as an example (and assuming no abbreviations are used), the size of the column may be relatively large (e.g., to hold up to 14 characters for the Carolinas), while a single byte code may be used to represent all 50 states, resulting in substantial compression of the column data.
On the other hand, if the column is not relatively large, the use of representations is disabled, at step 414. For example, if the states in the column are stored as 2 letter abbreviations, a single-byte code would only represent a two-to-one reduction, which may not justify the use of representations, considering it is the data alone that is, in effect, compressed by the representation, and not the rest of the query results message (header, checksum, etc). The operations 400 are exited, at step 416, for example, by returning an updated column status record 163.
As previously described, the server 147 may be configured to perform certain operations in order to implement the use of representations.
At step 504, a determination is made as to whether pre-formatted caching is enabled for the column, for example, by testing a flag in the column status record 163 associated with the column for which data is requested. As previously described, for some embodiments, the use of representations may be disabled when caching is disabled. Therefore, if caching is disabled, the actual data is sent, at step 508. Of course, for some embodiments, the use of representations may be enabled independently of pre-formatted caching. Regardless, even if caching is enabled, but the use of representations is disabled (e.g., the column is not large enough), as determined at step 506, the actual data is sent, at step 508.
If the use of representations is enabled, however, a determination is made, at step 510, as to whether a representation record 167′ for the actual requested data already exists. For example, the server 147 may search the column representation table 166′ for a column representation record 167′ for to the actual data. If a column representation record 167′ already exists, the representation is sent to the client 110, at step 516. If a representation 167′ does not exist, a representation is generated, at step 512, and, at step 514, a column representation record 167′ containing the newly generated representation is added to the column representation table 166′ (e.g., for use in processing a subsequent request), prior to returning the representation, at step 516. Any suitable techniques may be utilized to generate the representation, such as a the use of compression algorithms, any type of assignment algorithms, sequential numbering, or any other type function. Of importance is that each representation corresponds to a different distinct value of the column, and has fewer bytes.
Of course, the operations 500 are exemplary only and the illustrated operations may be varied for different embodiments. For example, for some embodiments, the decision to use representations for a column may be made at the server 147 rather than the client 110. Therefore, a server side process (e.g., the query optimizer 152) may examine the column size (e.g., similar to step 412 of
Regardless of whether the decision to use representations is made at the client or server, it is important to ensure that the column status tables 162/162′ and column representations tables 166/166′ are synchronized. For example, the client 110 needs to knows when the server 147 is sending a representation rather than the actual requested data, as well as the actual column value represented. For some embodiments, a protocol may be established to ensure that tables accessed by both the client 110 and server 147 are current. For example, when enabling/disabling pre-formatted caching or the use of representations for a column, the client 110 may send the corresponding column status record 163 to the server 147 for use in updating/replacing a column status record 163′. In a similar manner, when the server creates a new representation, the associated representation record 166 may be sent to the client to add to the client-side cache.
While the conventional use of database indexes has been limited to providing statistics (e.g., column-level statistics) regarding distribution of data to a query optimizer in an effort to enhance searching, aspects of the present invention extend the use of database indexes to a requesting client. For example, the client may access indexes (or other type objects that provide information regarding distribution of data in a database) in an effort to enhance the manipulation and/or access of requested data. Data likely to be returned often (e.g., as indicated by a relatively low number of distinct values in a column) may be pre-formatted and stored in a cache. Upon receiving data, rather than formatting the received data, the client may retrieve pre-formatted data from the cache, thereby reducing processing overhead. For some embodiments, the client may also determine that data likely to be returned is relatively large (i.e., high number of bytes). The client may request that a relatively small representation (i.e., fewer bytes) of the data be sent instead of the actual data, thus increasing the number of rows returned in each block and thereby reducing network traffic between the client and server.
While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.
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|U.S. Classification||1/1, 719/316, 707/E17.005, 707/999.101, 707/999.01, 707/999.102, 707/999.202, 707/999.103, 707/999.104|
|International Classification||G06F17/30, G06F3/00|
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|Mar 13, 2003||AS||Assignment|
Owner name: INTERNATIONAL BUSINESS MACHINES CORPORATION, NEW Y
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:SANTOSUOSSO, JOHN M.;REEL/FRAME:013876/0400
Effective date: 20030306
|Dec 30, 2009||FPAY||Fee payment|
Year of fee payment: 4
|May 16, 2014||REMI||Maintenance fee reminder mailed|
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